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  2. Level of measurement - Wikipedia

    en.wikipedia.org/wiki/Level_of_measurement

    Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio.

  3. Continuous or discrete variable - Wikipedia

    en.wikipedia.org/.../Continuous_or_discrete_variable

    In mathematics and statistics, a quantitative variable may be continuous or discrete if it is typically obtained by measuring or counting, respectively. [1] If it can take on two particular real values such that it can also take on all real values between them (including values that are arbitrarily or infinitesimally close together), the variable is continuous in that interval. [2]

  4. Statistical data type - Wikipedia

    en.wikipedia.org/wiki/Statistical_data_type

    Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature.

  5. Scale (social sciences) - Wikipedia

    en.wikipedia.org/wiki/Scale_(social_sciences)

    Visual analogue scale (also called the Continuous rating scale and the graphic rating scale) – respondents rate items by placing a mark on a line. The line is usually labeled at each end. There are sometimes a series of numbers, called scale points, (say, from zero to 100) under the line.

  6. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    Entropy: While the entropy of a discrete variable is location-invariant and scale-independent, and therefore not a measure of dispersion in the above sense, the entropy of a continuous variable is location invariant and additive in scale: If () is the entropy of a continuous variable and = +, then () = + ⁡ ().

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature.

  8. Ordinal data - Wikipedia

    en.wikipedia.org/wiki/Ordinal_data

    Ordinal data is a categorical, statistical data type where the variables have natural, ordered categories and the distances between the categories are not known. [1]: 2 These data exist on an ordinal scale, one of four levels of measurement described by S. S. Stevens in 1946.

  9. Moderation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Moderation_(statistics)

    If the first independent variable is a categorical variable (e.g. gender) and the second is a continuous variable (e.g. scores on the Satisfaction With Life Scale (SWLS)), then b 1 represents the difference in the dependent variable between males and females when life satisfaction is zero. However, a zero score on the Satisfaction With Life ...